Comparative study of neural networks and least mean square algorithm applied to the optimization of cosmetic formulations

Abstract

In this work, a comparative study between two methods to acquire relevant information about a cosmetic formulation has been carried out. A Design of Experiments (DOE) has been applied in two stages to a capillary cosmetic cream: first, a Plackett-Burman (PB) design has been used to reduce the number of variables to be studied; second, a complete factorial design has been implemented. With the experimental data collected from the DOE, a Least Mean Square (LMS) algorithm and Artificial Neural Networks (ANN) have been utilized to obtain an equation (or model) that could explain cream viscosity. Calculations have shown that ANN are the best prediction method to fit a model to experimental data, within the interval of concentrations defined by the whole set of experiments.

Optimization‐based cosmetic formulation: Integration of mechanistic model, surrogate model, and heuristics

“…When the historical data are scarce, additional data sampling is required. By far, many efficient sampling approaches have been used in the cosmetic industry such as Latin‐hypercube sampling, Plackett‐Burman, full‐fractional, and so forth 37,38 . Referring to the “one in ten” rule, the number of data samples is preferably 10 times more than the number of ingredient candidates.…”

Effect of ionic composition on thermal properties of energetic ionic liquids

“…First, a hybrid approach was used to determine the optimal subset of descriptors by combining regression with the least-mean square algorithm (LS) 27 or the genetic algorithm (GA) 28 as an optimization method. The Multiple linear regression (MLR) analysis (Eq.…”

The Composition and Development of Moisturizers

“…reducing "tackiness" in use could involve introduction of a silicone, reduction or change in a particular wax or oil or all of these. Success is driven by the experience of the formulator and their knowledge of the attributes of the raw materials at their disposal, though mathematical models have been used to optimize formulation characteristics [ 103 ] .…”